Cost-effectiveness of precision medicine in gastrointestinal stromal tumor and gastric adenocarcinoma

Infiltration and Significance of CD103+CD8+ T Cells in Gastrointestinal Adenocarcinoma

Immunohistochemical staining is a common technique to study tissue morphology and in situ protein expression. With the rise of immunotherapy, more and more markers in the tumor microenvironment have been discovered. In this paper, the multiplex immunofluorescence staining method was used to stain paraffin sections of 35 cases of gastric adenocarcinoma tissue and 35 cases of colorectal adenocarcinoma tissue and its adjacent tissue. The infiltration of CD8+ T cells and CD103+CD8+ T cells in the slices was detected by using the slice scanner to form the map and CaseViewer2.0 software analysis. The experimental results in this paper showed that compared with adjacent tissues, the infiltration degree of CD8+ T cells in gastric adenocarcinoma tissue was significantly lower (Z = 2.244, P = 0.025, P < 0.05), and the infiltration degree of cells was significantly lower (Z = 2.785, P = 0.005, P < 0.05). In gastric adenocarcinoma tissue, the infiltration of CD8+ T cells was correlated with the tumor diameter of gastric adenocarcinoma (P = 0.002). There was a statistically significant difference. The degree of CD103+CD8+ T cell infiltration was related to the survival of patients with gastric adenocarcinoma (P = 0.002) and the degree of tumor differentiation (P = 0.004). The infiltration of CD103+CD8+ T cells in gastric cancer tissue and colorectal cancer tissue is related to the survival of patients. CD103+CD8+ T cells are thought to play a role in the prognosis of gastric adenocarcinoma and colorectal adenocarcinoma. Experiments have shown that the more the CD103+CD8+ T cells, the better the prognosis of gastric adenocarcinoma and colorectal adenocarcinoma, so the prognosis of gastric adenocarcinoma and colorectal adenocarcinoma can be improved by increasing CD103+CD8+ T cells.

Identification of lncRNA-associated competing endogenous RNA networks for occurrence and prognosis of gastric carcinoma

Background

Gastric cancer (GC) is one of the common digestive malignancies worldwide and causes a severe public health issue. So far, the underlying mechanisms of GC are largely unclear. Thus, we aim to identify the long non‐coding RNA (lncRNA)‐associated competing endogenous RNA (ceRNA) for GC.

Methods

TCGA database was downloaded and used for the identification of differentially expressed (DE) lncRNAs, miRNAs, and mRNAs, respectively. Then, the ceRNA network was constructed via multiple online datasets and approaches. In addition, various in vitro assays were carried out to validate the effect of certain hub lncRNAs.

Results

We constructed a ceRNA network, including 76 lncRNAs, 18 miRNAs, and 159 mRNAs, which involved multiple critical pathways. Next, univariate and multivariate analysis demonstrated 11 lncRNAs, including LINC02731, MIR99AHG, INHBA‐AS1, CCDC144NL‐AS1, VLDLR‐AS1, LIFR‐AS1, A2M‐AS1, LINC01537, and LINC00702, and were associated with OS, and nine of those lncRNAs were considered as hub lncRNAs involved in the sub‐ceRNA network. The in vitro assay indicated two lncRNAs, INHBA‐AS1 and CCDC144NL‐AS1, which were positively related to the GC aggressive features, including proliferation, invasion, and migration.

Conclusions

We identified nine hub lncRNAs and the associated ceRNA network related to the prognosis of GC, and then validated two out of them as promising oncogenes in GC.

Circular RNA hsa_circ_0110389 promotes gastric cancer progression through upregulating SORT1 via sponging miR-127-5p and miR-136-5p

Increasing studies have found that circular RNAs (circRNAs) are aberrantly expressed and play important roles in the occurrence and development of human cancers. However, the function of circRNAs on environmental carcinogen-induced gastric cancer (GC) progression remains poorly elucidated. In the present study, hsa_circ_0110389 was identified as a novel upregulated circRNA in malignant-transformed GC cells through RNA-seq, and subsequent quantitative real-time PCR verified that hsa_circ_0110389 was significantly increased in GC tissues and cells. High hsa_circ_0110389 expression associates with advanced stages of GC and predicts poor prognosis. Knockdown and overexpression assays demonstrated that hsa_circ_0110389 regulates proliferation, migration, and invasion of GC cells in vitro. In addition, hsa_circ_0110389 was identified to sponge both miR-127-5p and miR-136-5p and SORT1 was validated as a direct target of miR-127-5p and miR-136-5p through multiple mechanism assays; moreover, hsa_circ_0110389 sponged miR-127-5p/miR-136-5p to upregulate SORT1 expression and hsa_circ_0110389 promoted GC progression through the miR-127-5p/miR-136-5p-SORT1 pathway. Finally, hsa_circ_0110389 knockdown suppressed GC growth in vivo. Taken together, our findings firstly identify the role of hsa_circ_0110389 in GC progression, which is through miR-127-5p/miR-136-5p-SORT1 pathway, and our study provides novel insight for the identification of diagnostic/prognostic biomarkers and therapeutic targets for GC.

CT Image Examination Based on Virtual Reality Analysis in Clinical Diagnosis of Gastrointestinal Stromal Tumors

With the advancement and development of medical equipment, CT images have become a common lung examination tool. This article mainly studies the application of CT imaging examination based on virtual reality analysis in the clinical diagnosis of gastrointestinal stromal tumors. Before extracting suspected lymph nodes from a CT image of the stomach, the CT image sequence is preprocessed first, which can reduce the cumbersomeness of subsequent extraction of suspected lymph nodes and speed up the subsequent processing. According to medical knowledge, CT images of the stomach show that lymph nodes mainly exist in the adipose tissue around the gastric wall, but there are no lymph nodes in the subcutaneous fat outside the chest. The most basic gray value in the image and the neighborhood average difference feature related to gray level are used as the primary features of visual attention detection. When extracting the neighborhood average difference feature, we use a 3 ∗ 3 sliding window method to traverse each point of the pixel matrix in the image, thereby calculating the feature value of each pixel in the image. After the feature extraction is completed, it is necessary to calibrate the data and make a training data set. The SP immunohistochemical staining method was used. The specimens were fixed with 10% formaldehyde, routinely embedded in paraffin, sectioned, and stained with HE. The tumor tissue was determined by immunohistochemistry, and the reagents were products of Maixin Company. All patients were followed up by regular outpatient review, letters, and visits or phone calls. The data showed that immunohistochemical tumor cells showed positive staining for CD117 (14/15, 93.3%) and CD34 (10/15, 66.7%). The results show that the application of virtual reality technology to CT imaging examination can significantly improve the diagnostic accuracy of gastrointestinal stromal tumors.

Difference in Perfusion Parameters Between Gastric Cancer and Gastric Stromal Tumors: Evaluation With Oral Contrast Plus Contrast-Enhanced Ultrasonography

Objective: To explore the difference of perfusion parameters between gastric cancer (GC) and gastric stromal tumors (GSTs) by using oral contrast plus contrast-enhanced ultrasonography (OC+CEUS).

Methods: We retrospectively reviewed 149 patients with histologically confirmed gastric lesions (80 patients with GC and 69 patients with GST). OC+CEUS was performed in all patients in the GC group and the GST group before surgery. The cine loops of OC+CEUS of all cases were analyzed. The perfusion parameters including arrival time (AT), time to peak (TTP), basal intensity (BI), and peak intensity (PI) were obtained via a program designed for autotracking contrast quantification (ACQ). The between-group differences in these parameters were compared.

Results: According to time-intensity curve (TIC) analysis, high-risk GST had higher PI than low-risk GST (P < 0.05). GC had faster AT and higher PI than normal gastric wall (P < 0.05); GST had higher PI than normal gastric wall (P < 0.05). Furthermore, the GC group had faster AT and higher PI than the GST group (P < 0.05). In contrast, the difference in BI and peak time (TTP) between the groups was not significant (P > 0.05).

Conclusion: AT and PI differ significantly between the GC group and the GST group. As a new method, OC+CEUS has value for the differential diagnosis of GC and GST.

Cost-effectiveness analysis of ramucirumab treatment for patients with hepatocellular carcinoma who progressed on sorafenib with α-fetoprotein concentrations of at least 400 ng/ml

Objective: This study aimed to compare the cost-effectiveness of ramucirumab versus placebo for patients with hepatocellular carcinoma who progressed on sorafenib with α-fetoprotein concentrations (AFP) of at least 400 ng/ml in the United States.Methods: A Markov model was constructed to assess the cost-effectiveness of ramucirumab. Health outcomes were measured as quality-adjusted life years (QALYs). With TreeAge software, the disease process was modeled as three health states: progression-free survival (PFS), progressive disease (PD), and death. Costs were extracted from the REACH-2 trial, and utility was derived from published literature. Incremental cost-effectiveness ratios (ICERs) were calculated to compare ramucirumab with placebo. Probabilistic sensitivity analyses were developed to examine the robustness of the results.Results: In the base case analysis, ramucirumab therapy had a cost of $55,508.41 and generated 0.54 QALYs, while placebo therapy had a cost of $761.09 and generated 0.47 QALYs, leading to an additional $54,747.32 in costs and 0.07 QALYs. The ICER was $782,104.57 per QALY, which was much higher than the willingness-to-pay threshold of $100,000 per QALY. According to sensitivity analyses, the utility of PD in the two groups was the dominant parameter influencing the ICER.Conclusion: Although ramucirumab was associated with prolonged survival for patients with advanced hepatocellular carcinoma who progressed on sorafenib treatment with an AFP of at least 400 ng/ml, it is not a cost-effective treatment from a United States payer perspective.

Long non-coding RNA polymorphisms on 8q24 are associated with the prognosis of gastric cancer in a Chinese population

Background

Gastric cancer (GC) remains the third leading cause of cancer death in China. Although genome-wide association studies have identified the association between several single nucleotide polymorphisms (SNPs) on 8q24 and the risk of GC, the role of these SNPs in the prognosis of GC in Chinese populations has not yet been fully evaluated. Therefore, this study was conducted to explore the association between long non-coding RNA (lncRNA) polymorphisms on 8q24 and the prognosis of GC.

Methods

We genotyped 726 surgically resected GC patients to explore the association between eight SNPs in the lncRNAs CCAT1 (rs10087719, rs7816475), PCAT1 (rs1026411), PRNCR1 (rs12682421, rs13252298), and CASC8 (rs1562430, rs4871789, rs6983267) transcribed from the 8q24 locus and the prognosis of GC in a Chinese population.

Results

We found that the patients carrying rs12682421 AA genotypes survived for a shorter time than those with the GG/GA genotype (HR = 1.39, 95% confidence interval (CI) [1.09-1.78]). Compared with the CC/CT genotype, the TT genotype of rs1562430 was associated with an increased risk of death (HR = 1.38, 95% CI [1.06-1.80]). Furthermore, the results also identified the rs1026411 SNP as an independent prognostic factor for poor survival in GC patients. Patients carrying AA/AG variant genotypes had a 36% increased risk of death compared to those carrying the GG genotype (HR = 1.36, 95% CI [1.06-1.74]). These findings suggested that the rs12682421, rs1026411 and rs1562430 SNPs may contribute to the survival of GC and be prognostic markers for GC.

Gastrointestinal Stromal Tumors of the Stomach and Esophagus

Gastrointestinal stromal tumors (GISTs) arise anywhere along the gastrointestinal tract, most commonly as a result of c-kit or PDGFRA proto-oncogene mutations. Surgical resection is an important component of treatment. However, molecular profiling of GISTs has provided many insights into adjuvant and neoadjuvant therapy options. Imatinib, the most frequently studied medical therapy, has been shown in numerous studies to provide benefit to patients in both the neoadjuvant and adjuvant setting. Interval imaging is an important component of the treatment of GISTs and national surveillance recommendations should be followed.

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics data, are indispensable to glean into the cancer genome and proteome and these approaches have generated multidimensional universal studies of genes and proteins (OMICS) data which has the potential to facilitate precision medicine. However, due to slow progress in computational technologies, the translation of big omics data into their clinical aspects have been slow. In this review, attempts have been made to describe the role of high-throughput genomic and proteomic technologies in identifying a panel of biomarkers which could be used for the early diagnosis and prognosis of cancer.